This article presents a method, based on orbital remote sensing, to map the extent of forest plantations in São Paulo State (Southeast Brazil). The proposed method uses the random forest machine learning algorithm available on the Google Earth Engine (GEE) cloud computing platform. We used 30 m annual mosaics derived from Landsat-5 Thematic Mapper (TM) images and from Landsat-8 Operational Land Imager (OLI) images for the 1985 to 1995 and 2013 to 2021 time periods, respectively. These time periods were selected based on the planted areas’ rotation, especially the eucalypt’s short rotation. To classify the forest plantations, green, red, NIR, and MIR spectral bands, NDVI, GNDVI, NDWI, and NBR spectral indices, and vegetation, shade, and soil fractions were used for both sensors. These indices and the fraction images have the advantage of reducing the volume of data to be analyzed and highlighting the forest plantations’ characteristics. In addition, we also generated one mosaic for each fraction image for the TM and OLI datasets by computing the maximum value through the period analyzed, facilitating the classification of areas occupied by forest plantations in the study area. The proposed method allowed us to classify the areas occupied by two forest plantation classes: eucalypt and pine. The results of the proposed method compared with the forest plantation areas extracted from the land use and land cover maps, provided by the MapBiomas product, presented the Kappa values of 0.54 and 0.69 for 1995 and 2020, respectively. In addition, two pilot areas were used to evaluate the classification maps and to monitor the phenological stages of eucalypt and pine plantations, showing the rotation cycle of these plantations. The results are very useful for planning and managing planted forests by commercial companies and can contribute to developing an automatic method to map forest plantations on regional and global scales.
RESUMO: Este artigo aborda a utilização de imagens de satélites como suporte para evidenciar a expansão histórico-cartográfica das fronteiras paulistas entre o descobrimento do Brasil e a sua independência, recurso esse utilizado na exposição Cartografia de uma história, realizada no Museu Paulista da USP em 2005. As imagens foram aquelas do Modis, do Shuttle Radar Topographic Mission e do Satélite Landsat-5. As cenas foram georreferenciadas valendo-se da ferramenta Spring e dos mosaicos georretificados disponibilizados pela Nasa. Sobre estes produtos foi lançado um valioso conjunto de informações cartográficas coletadas pelas pesquisadoras da Cátedra Jaime Cortesão da USP. O conjunto inclui o Tratado de Tordesilhas, com suas distorções, o Mapa das Cortes, as capitanias, as bandeiras, as monções, as trilhas, os tropeirismos, ou seja, todo o conjunto de ações pioneiras que permitiram consolidar o território paulista e grande parte da identidade espacial brasileira. Foram analisados também o mito da Ilha Brasil e os enlaces das bacias do rio Amazonas e do rio Paraná-Prata a partir dos atributos geomorfológicos dispostos nas imagens orbitais. Os resultados foram consolidados em um banco de dados de 800 megabites, sendo dispostos em exposição junto ao Museu Paulista. Este artigo descreve os procedimentos metodológicos de geração e de análise das imagens bem como sintetiza os resultados alcançados. PALAVRAS-CHAVE: Sensoriamento Remoto. Cartografia Histórica. Museu Paulista. Expansão Paulista. América Portuguesa.ABSTRACT: This article discusses the use of satellite imaging as a means to support and map out the historical expansion of the borders of São Paulo State between the discovery of Brazil and its independence. This tool was employed in Cartography of a history, an exhibition staged at Museu Paulista/USP in 2005. The images were generated by Modis, Shuttle Radar
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